Detection of looming is a critical for successful collision avoidance. Regan et al (1979 – 96) has been foremost in documenting humans‘ sensitivity to looming and MiD, but there are various methodological factors that make it difficult to extrapolate from these measures to performance in natural settings. The current study was concerned with looming thresholds in the context of roadside behaviour. Adaptive (BEST-PEST) staircase procedures were run using photo-realistic images of a motorbike or car presented for 200ms, in order to determine sensitivity to looming of vehicles in central or peripheral vision, under monocular viewing conditions and against a neural grey background or a realistic static road scene. Two critical TTC arrival time values were simulated: 5s (sufficient time to cross) & 3s (critical decision point). Vehicle images changed in size and expansion to simulate approach at different speeds, within a display configuration that ensured sufficient pixel resolution for all trials/steps. The participant's task was simple detection of looming (opponent edge motion) for a vehicle image when there was also lateral translation of the image. Thresholds for looming in these conditions were substantially higher than those reported by Regan et al under more constrained psychophysical conditions. We also found a significant increase in thresholds when stimuli were presented only 6deg in the periphery. The results suggest that, in displays that contain the contrast and edge-detail of natural scenes, and where other motion information may be present, the detection of looming may be significantly poorer than previously reported. This still allows for accurate detection if the object is foveated, but if in a cluttered scene the observer glances slightly off-target they may fail to detect fast approaching vehicles. This may be particularly a problem for smaller profile vehicles such as motorcycles and may explain driver errors with respect to these.